Spectral analysis of living tissue can be used to detect various forms of cancer and other types of diseases. In spectral analysis, light illuminates a tissue region under examination and a light detector detects optical properties of the illuminated tissue region by measuring light energy modified by its interaction with the tissue region in a pre-determined frequency and amplitude domain. Optical properties include absorption, luminescence, fluorescence, frequency and time domain response to various materials injected to the tissue region and other electromagnetic responses. Diseased tissue may be identified by comparing a spectrum obtained to spectra of normal tissue obtained under the same controlled conditions.
Traditional image sensors include a two dimensional array of photo-detectors (pixels) that are accessed individually by electronics on the same chip, or external to the chip. A black and white image is formed by digitizing the amplitude of each pixel, which creates a gray scale. Color images function in a similar manner, but employ complex algorithms to compute the color. One common color sensor has a color mask that is placed on the image sensor. The color mask is a light filter that allows only certain light wavelengths to penetrate and reach the detector. Then, by comparing amplitudes of adjacent pixels, the color is calculated.
One disadvantage of conventional image sensors is size due to the number of pixels (photo-detectors) required to produce a quality image. Another disadvantage of conventional image sensors is the complex electronics involved in addressing each pixel (photo-detector).